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Pathogenic and Indigenous Denitrifying Bacteria are Transcriptionally Active and Key Multi-Antibiotic-Resistant Players in Wastewater Treatment Plants

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... However, these approaches disregard bacterial viability and lack phenotypic validation, i.e. we can generally not con rm that resistance genes inferred from metagenomics data really confer a resistance phenotype in their host [53,54]. It is also generally di cult to relate metagenomic resistomes to resistant clinical pathogens or non-native bacteria released into the environment, although metagenome-assembled genomes (MAG) reconstruction provides new opportunities [55]. In this study, we propose a combination of phenotypically selective cultivation and the brute-force genotypic and metagenomics-based analyses of microbial communities that organically links active resistance phenotypes to their genotypes which we termed "phenotypic metagenomics". ...
... Recent investigations have provided some consensus on the impacts of WWTP discharge on the river antibiotic resistome or speci c resistance genes [9,55]. However, whether ESBL-producing and/or carbapenem-resistant bacteria that are discharged with WWTP e uents are eliminated in the environment or are instead persisting, invading other environments, or are even locally selected in the diverse patchwork of local microbiomes found in rivers remains elusive. ...
... This change is of particular importance for wastewater treatment, which dramatically reduces the abundance of most beta-lactamase genes and families (see the Page 11/23 red circles with log 2 (SEF) < 0 indicating abundance decrease, Figure 5a), revealing an important role of WWTPs as a barrier to prevent most enteric beta-lactamase resistance from entering the receiving environment. This result con rms and complements previous results indicating a considerable qualitative and quantitative resistome ltering function of WWTPs [4,55]. On the other hand, the differentiation in resistome composition across habitats agrees with recent evidence for bacterial composition as a key deterministic driver of resistomes across human and environmental habitats [4,57]. ...
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Background The abundance of clinically important antibiotic resistance determinants in wastewater has raised concerns regarding their dissemination into the environment and transmission to animals and humans. However, the high bacterial diversity and complexity of environmental microbiomes makes it challenging to comprehensively detect and quantify clinically relevant resistance determinants. To tackle this outstanding technical bottleneck, classic phenotype-based approaches vastly underestimate the diversity of clinically relevant resistance in environmental reservoirs, while increasingly applied genotyping-based approaches alone usually fail to capture information on the resistance phenotype, viability, and activities of resistant bacteria. Results Here, we developed phenotypic metagenomics as a novel high-throughput approach to couple selective cultivation (phenotyping) and metagenomics (genotyping) to overcome these difficulties of classic phenotype or genotype-based approaches. Using this new method, we were able to track the invasion of wastewater-born multi-resistant opportunistic pathogens into river sediment and epilithic biofilm in 9 Swiss rivers downstream of wastewater treatment plants (WWTPs). The results show that WWTPs release clinically important carbapenem-resistant opportunistic pathogens and promotes the spread of extended-spectrum beta-lactamase resistance genes in the receiving river water. Especially, epilithic biofilms were identified as an unrecognized environmental reservoir of wastewater-associated carbapenem resistant bacteria, which appear to also invade the gut of amphipods, a group of generalist invertebrate in local rivers. We further used metagenome-assembled genomes to characterize phenotypically resistant bacteria and their extended-spectrum beta-lactamase and carbapenemase resistance genes to confirm our finding that wastewater effluent increases resistance levels of extended-spectrum beta-lactamases in the receiving river water. Conclusions This study demonstrates that where culture plating and culture-independent metagenomics fail individually, their complementary combination allows tracking multi-resistant bacteria as they invade river habitats. The proof-of-concept approach that couple resistance phenotyping and genotyping provides a roadmap for sensitive, standardized, and cost-effective surveillance of the clinically relevant aspects of environmental resistomes. The findings call for a thorough life cycle assessment of the selection and transmission of last-resort antibiotic resistance determinants from clinical to environmental reservoirs.
... In clinical contexts, metatranscriptomics has been used to investigate ARG and VF expression profiles in human-associated microbial communities (Heravi et al., 2020;Zhang et al., 2020a). In wastewater treatment plants, the integration of metagenomic and transcriptomic data has been used to generate an overview of ARG expression in effluent microbiota (Ju et al., 2019), and showed that pathogenic and denitrifying bacteria are transcriptionally active (Yuan et al., 2021). However, the effects of xenobiotics on the expression profiles of ARGs and VFs in aquatic microbial communities are not known. ...
... For selection to be effective, these genes must be expressed. While metatranscriptome analysis has been used to examine the expression profiles of ARGs and VFs in the human microbiome (Heravi et al., 2020;Zhang et al., 2020a) and in WWTPs (Ju et al., 2019;Yuan et al., 2021), expression in aquatic ecosystems has not been examined in detail. ...
Article
Antibiotic resistance genes (ARGs) and virulence factors (VFs) are critical threats to human health. Their abundance in aquatic ecosystems is maintained and enhanced via selection driven by environmental xenobiotics. However, their activity and expression in these environments under xenobiotic stress remains unknown. Here ARG and VF expression profiles were examined in aquatic microcosms under ciprofloxacin, glyphosate and sertraline hydrochloride treatment. Ciprofloxacin increased total expression of ARGs, particularly multidrug resistance factors. Total expression of ARGs and VFs decreased significantly under glyphosate and sertraline treatments. However, in opportunistic human pathogens, these agents increased expression of both ARGs and VFs. Xenobiotic pollutants, such as the compounds we tested here, have the potential to disrupt microbial ecology, promote resistance, and increase risk to human health. This study systematically evaluated the effects of environmental xenobiotics on transcription of ARGs and VFs, both of which have direct relevance to human health. Transcription of such genes has been overlooked in previous studies.
... A recent study on the surveillance of different urban wastewater treatment plants (WWTPs) on the occurrence of ARGs shows that the pattern of ARGs present in the WWTPs reflects that of the prevalence of ARGs found in the clinic [1]. In another study, using a metatranscriptomic approach, Yuan et al reported the presence of ARGs against multiple classes of antibiotics in ≈ 45% of the isolated genomes from the influents and effluents of different WWTPs [2]. Similarly, uropathogenic Escherichia coli found in the effluent of WWTPs were reported to have adapted and hence resistant to the treatment [3]. ...
Article
Bacterial adaptation to external stress and its consequential evolution to antibiotic resistance (AR) poses a huge risk to the health sector. Conventional wastewater treatment and disinfection technologies may often end up disseminating AR to the environment. Although new technologies to treat water are emerging, AR and antibiotic tolerance induced by the treatment and the significance of bacterial adaptation is unclear. Here, we tested the impact of stress-adapted Salmonella Typhimurium on the efficacy of visible light-assisted sonophotocatalysis (SPC). We show that bacteria adapted to constant and increasing concentrations of kanamycin and hydrogen peroxide could survive SPC treatment for a longer period compared to that of the unadapted bacteria. Importantly, the selection of AR and antibiotic tolerance after the exposure to SPC were dependent on the initial stress adaptation. Transcriptomic analysis reveals that the high expression of flagellar genes in the bacteria subjected to sublethal SPC was counteracted by the genes associated with stress response and metabolism. Finally, SPC treated S. Typhimurium exhibited attenuation in the BALB/c mice model. Our results suggest that SPC is an efficient technique to inactivate S. Typhimurium in water although the efficacy of the system depends on the prior adaptation of the bacteria to external stress.
... A similar result was also reported in a recent study, in which potential pathogens and indigenous denitrifying bacteria in wastewater were identified as transcriptionally active hosts of multiresistance genes. 45 Hence, more attention should be paid to the prevalence and health risks of multiresistance in wastewater microbiota. After mating with E. coli K12, a total of 4200 CFU/mL colonies were observed on selective plates. ...
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The dissemination of plasmid-borne antibiotic resistance genes (ARGs) in wastewater is becoming an urgent concern. Previous studies mainly focused on the effects of coexisting contaminants on plasmid conjugation, but ignored the potential contribution of some byproducts inevitably released from wastewater treatment processes. Herein, we demonstrate for the first time that nitric oxide (NO), an intermediate of the wastewater nitrogen cycle, can significantly boost the conjugative transfer of plasmid RP4 from Escherichia coli K12 to different recipients (E. coli HB101, Salmonella typhimurium, and wastewater microbiota). Phenotypic and genotypic tests confirmed that NO-induced promotion was not attributed to the SOS response, a well-recognized driver for horizontal gene transfer. Instead, NO exposure increased the outer membrane permeability of both the donor and recipient by inhibiting the expression of key genes involved in lipopolysaccharide biosynthesis (such as waaJ), thereby lowering the membrane barrier for conjugation. On the other hand, NO exposure not only resulted in the accumulation of intracellular tryptophan but also triggered the deficiency of intracellular methionine, both of which were validated to play key roles in regulating the global regulatory genes (korA, korB, and trbA) of plasmid RP4, activating its encoding transfer apparatus (represented by trfAp and trbBp). Overall, our findings highlighted the risks of NO in spreading ARGs among wastewater microbiota and updated the regulation mechanism of plasmid conjugation.
... Most antibiotics are incompletely metabolized in living organisms, with about 30-90% of parent compounds (or metabolites) being excreted , resulting in large amounts of antibiotics remaining in wastewater, biosolids (i.e., sludge), and animal manures (Chen et al., 2014). There is widespread concern that environmental emissions of antibiotics may increase the development and dissemination of antibiotic resistance, which could pose serious risks to human and animal health (Terzic et al., 2018;Yuan et al., 2021). ...
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Erythromycin (ERY), a widely used macrolide antibiotic, is omnipresent in soil and aquatic environments, which may potentially contaminate food crops but remains to be explored. Two leafy vegetables, pakchoi (Brassica rapa subsp. chinensis) and water spinach (Ipomoea aquatica Forsk.), were grown in laboratory-constructed soil or hydroponic systems to investigate the dynamic accumulation of ERY in edible plants. Results indicate ¹⁴C-ERY could be absorbed by water spinach and pakchoi in both systems. Autoradiographic imaging and concentration data of plant tissues suggested that ERY had limited translocation from roots to shoots in these two vegetables. The accumulation level of ERY was similar between the two vegetables in the soil system; but in the hydroponic system, pakchoi had a higher ERY accumulation than water spinach, with the bioconcentration factor of 2.74–25.98 and 3.65–11.67 L kg⁻¹, respectively. The ERY intake via vegetable consumption was 0.01–2.17 ng kg⁻¹ day⁻¹, which was much lower than the maximum acceptable daily intake (700 ng kg⁻¹ day⁻¹), indicating negligible risks of consuming vegetables with roots exposed to ERY at environmentally relevant levels. In addition, ERY was found to cause growth inhibition and oxidative stress to pakchoi, even at low concentrations (7 and 22 μg L⁻¹). This work contributes to a better understanding of plant uptake and translocation of ERY in soils and water, and has important implications for the reasonable evaluation of the implied risks of ERY to vegetables and human health.
... According to Cai et al. [42], this applies, for instance, to around 80 % of sewage in India. Subsequently, potentially infectious and harmful parasitic microorganisms become widespread and form a threat to public health when present in drinking water, water recreation areas, and aquatic food production systems [42,[73][74][75]. Our results clearly show that biomonitoring of wastewater treatment efficiency via molecular methods ("-omics") can be greatly improved by using primer-independent shotgun approaches to ensure adequate detection of parasitic protists. ...
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Background During wastewater treatment, the wastewater microbiome facilitates the degradation of organic matter, reduction of nutrients, and removal of gut parasites. While the latter function is essential to minimize public health risks, the range of parasites involved and how they are removed is still poorly understood. Results Using shotgun metagenomic (DNA) and metatranscriptomic (RNA) sequencing data from ten wastewater treatment plants in Switzerland, we were able to assess the entire wastewater microbiome, including the often neglected microeukaryotes (protists). In the latter group, we found a surprising richness and relative abundance of active parasites, particularly in the inflow. Using network analysis, we tracked these taxa across the various treatment compartments and linked their removal to trophic interactions. Conclusions Our results indicate that the combination of DNA and RNA data is essential for assessing the full spectrum of taxa present in wastewater. In particular, we shed light on an important but poorly understood function of wastewater treatment – parasite removal.
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Antibiotic resistance genes (ARGs) have become an important public health concern. Particularly, although several ARGs have been identified in wastewater treatment plants (WWTPs), very few studies have characterized their impacts on reactor performance. Therefore, our study sought to investigate the effect of a representative conjugative transfer plasmid (RP4) encoding multidrug resistance genes on ammonia oxidation. To achieve this, we established sequencing batch reactors (SBRs) and a conjugation model with E. coli donor strains carrying the RP4 plasmid and a typical ammonia-oxidating (AOB) bacterial strain (Nitrosomonas europaea ATCC 25978) as a recipient to investigate the effect of conjugative transfer of plasmid RP4 on AOB. Our findings demonstrated that the RP4 plasmid carried by the donor strains could be transferred to AOB in the SBR and to Nitrosomonas europaea ATCC 25978. In SBR treated with donor strains carrying the RP4 plasmid, ammonia removal efficiency continuously decreased to 71%. Once the RP4 plasmid entered N. europaea ATCC 25978 in the conjugation model, ammonia removal was significantly inhibited and nitrite generation was decreased. Furthermore, the expression of several functional genes related to ammonia oxidation in AOB was suppressed following the transfer of the RP4 plasmid, including amoA, amoC, hao, nirK, and norB. In contrast, the cytL gene encoding cytochrome P460 was upregulated. These results demonstrated the ecological risk of ARGs in WWTPs, and therefore measures must be taken to avoid their transfer.
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Taxonomy is an organizing principle of biology and is ideally based on evolutionary relationships among organisms. Development of a robust bacterial taxonomy has been hindered by an inability to obtain most bacteria in pure culture and, to a lesser extent, by the historical use of phenotypes to guide classification. Culture-independent sequencing technologies have matured sufficiently that a comprehensive genome-based taxonomy is now possible. We used a concatenated protein phylogeny as the basis for a bacterial taxonomy that conservatively removes polyphyletic groups and normalizes taxonomic ranks on the basis of relative evolutionary divergence. Under this approach, 58% of the 94,759 genomes comprising the Genome Taxonomy Database had changes to their existing taxonomy. This result includes the description of 99 phyla, including six major monophyletic units from the subdivision of the Proteobacteria, and amalgamation of the Candidate Phyla Radiation into a single phylum. Our taxonomy should enable improved classification of uncultured bacteria and provide a sound basis for ecological and evolutionary studies.
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Here we used flow cytometry (FCM) and filtration paired with amplicon sequencing to determine the abundance and composition of small low nucleic acid (LNA)-content bacteria in a variety of freshwater ecosystems. We found that FCM clusters associated with LNA-content bacteria were ubiquitous across several ecosystems, varying from 50 to 90% of aquatic bacteria. Using filter-size separation, we separated small LNA-content bacteria (passing 0.4 µm filter) from large bacteria (captured on 0.4 µm filter) and characterized communities with 16S amplicon sequencing. Small and large bacteria each represented different sub-communities within the ecosystems' community. Moreover, we were able to identify individual operational taxonomical units (OTUs) that appeared exclusively with small bacteria (434 OTUs) or exclusively with large bacteria (441 OTUs). Surprisingly, these exclusive OTUs clustered at the phylum level, with many OTUs appearing exclusively with small bacteria identified as candidate phyla (i.e. lacking cultured representatives) and symbionts. We propose that LNA-content bacteria observed with FCM encompass several previously characterized categories of bacteria (ultramicrobacteria, ultra-small bacteria, candidate phyla radiation) that share many traits including small size and metabolic dependencies on other microorganisms.
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Background: Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Results: Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. Conclusions: The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The DeepARG models and database are available as a command line version and as a Web service at http://bench.cs.vt.edu/deeparg .
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Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. While this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of 'marker' genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate, single cell and metagenome derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination, and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities. Published by Cold Spring Harbor Laboratory Press.
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Antibiotic resistance is a threat to human and animal health worldwide, and key measures are required to reduce the risks posed by antibiotic resistance genes that occur in the environment. These measures include the identification of critical points of control, the development of reliable surveillance and risk assessment procedures, and the implementation of technological solutions that can prevent environmental contamination with antibiotic resistant bacteria and genes. In this Opinion article, we discuss the main knowledge gaps, the future research needs and the policy and management options that should be prioritized to tackle antibiotic resistance in the environment.
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Understanding environmental and biological influences on the dynamics of microbial communities has received great attention in microbial ecology. Here, utilizing large time-series 16S rRNA gene data, we show that in activated sludge of an environmentally important municipal wastewater treatment plant, 5-year temporal dynamics of bacterial community shows no significant seasonal succession, but is consistent with deterministic assemblage by taxonomic relatedness. Biological interactions are dominant drivers in determining the bacterial community assembly, whereas environmental conditions (mainly sludge retention time and inorganic nitrogen) partially explain phylogenetic and quantitative variances and indirectly influence bacterial assembly. We demonstrate a correlation-based statistical method to integrate bacterial association networks with their taxonomic affiliations to predict community-wide co-occurrence and co-exclusion patterns. The results show that although taxonomically closely related bacteria tend to positively co-occur (for example, out of a cooperative relationship), negative co-excluding correlations are deterministically observed between taxonomically less related species, probably implicating roles of competition in determining bacterial assembly. Overall, disclosures of the positive and negative species-species relations will improve our understanding of ecological niches occupied by unknown species and help to predict their biological functions in ecosystems.
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Ancient and diverse antibiotic resistance genes (ARGs) have previously been identified from soil, including genes identical to those in human pathogens. Despite the apparent overlap between soil and clinical resistomes, factors influencing ARG composition in soil and their movement between genomes and habitats remain largely unknown. General metagenome functions often correlate with the underlying structure of bacterial communities. However, ARGs are proposed to be highly mobile, prompting speculation that resistomes may not correlate with phylogenetic signatures or ecological divisions. To investigate these relationships, we performed functional metagenomic selections for resistance to 18 antibiotics from 18 agricultural and grassland soils. The 2,895 ARGs we discovered were mostly new, and represent all major resistance mechanisms. We demonstrate that distinct soil types harbour distinct resistomes, and that the addition of nitrogen fertilizer strongly influenced soil ARG content. Resistome composition also correlated with microbial phylogenetic and taxonomic structure, both across and within soil types. Consistent with this strong correlation, mobility elements (genes responsible for horizontal gene transfer between bacteria such as transposases and integrases) syntenic with ARGs were rare in soil by comparison with sequenced pathogens, suggesting that ARGs may not transfer between soil bacteria as readily as is observed between human pathogens. Together, our results indicate that bacterial community composition is the primary determinant of soil ARG content, challenging previous hypotheses that horizontal gene transfer effectively decouples resistomes from phylogeny.
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The presence of antibiotics can exert significant selection pressure on the emergence and spread of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria (ARB). However, co-selection effects for ARGs, the mobility of ARGs and the identification of ARG hosts under high antibiotic selection pressures are poorly understood. Here, metagenomic assembly and binning approaches were used to comprehensively decipher the prevalence of ARGs and their potential mobility and hosts in activated sludge reactors treating antibiotic production wastewater. We found the abundance of different ARG types in antibiotic treatments varied greatly and certain antibiotic pressure promoted the co-selection for the non-corresponding types of ARGs. Antibiotic selection pressures significantly increased the abundance and proportions of ARGs mediated by plasmids (57.9%), which were more prevalent than those encoded in chromosomes (19.2%). The results indicated that plasmids and chromosomes had a tendency to carry different types of ARGs. Moreover, higher co-occurrence frequency of ARGs and MGEs revealed that antibiotics enhanced the mobility potential of ARGs mediated by both plasmids and integrative and conjugative elements. Among the 689 metagenome-assembled genomes (MAGs) with high estimated quality, 119 MAGs assigning to nine bacterial phyla were identified as the ARG hosts and 33 MAGs exhibited possible multi-resistance to antibiotics. Some ARG types tended to be carried by certain bacteria (e.g. bacitracin resistance genes carried by the family Burkholderiaceae) and thus showed a pronounced host-specific pattern. This study enhances the understanding of the mobility and hosts of ARGs and provides important insights into the risk assessment and management of antibiotic resistance.
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Shotgun metagenomic sequencing has revolutionized our ability to detect and characterize the diversity and function of complex microbial communities. In this review, we highlight the benefits of using metagenomics as well as the breadth of conclusions that can be made using currently available analytical tools, such as greater resolution of species and strains across phyla and functional content, while highlighting challenges of metagenomic data analysis. Major challenges remain in annotating function, given the dearth of functional databases for environmental bacteria compared to model organisms, and the technical difficulties of metagenome assembly and phasing in heterogeneous environmental samples. In the future, improvements and innovation in technology and methodology will lead to lowered costs. Data integration using multiple technological platforms will lead to a better understanding of how to harness metagenomes. Subsequently, we will be able not only to characterize complex microbiomes but also able to manipulate communities to achieve prosperous outcomes for health, agriculture, and environmental sustainability. Expected final online publication date for the Annual Review of Microbiology, Volume 74 is September 8, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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The coexistence of nitrate and antibiotics in wastewater is a common problem. The study aimed to explore response of denitrifying community, denitrification genes and antibiotic resistance genes (ARGs) to oxytetracycline (OTC) stress in polycaprolactone (PCL) supported solid-phase denitrification (SPD) reactors. Complete nitrate reduction (> 99%) was achieved in SPD system with OTC stress of 0, 0.05, 0.25 and 1 mg L⁻¹ during three-month operation, while it significantly declined by about 5% at a further increased OTC level of 5 mg L⁻¹. The efficient denitrification strongly related with a rich diversity of denitrifiers, while the abundances of which dramatically reduced as the OTC concentration reached ≥ 0.25 mg L⁻¹, which caused significant decline of denitrification genes, especially for narH, narJ, narI nirD, nosZ, and norB. Tetracycline resistance genes were a major type of promoted ARGs by different OTC stress, mainly related with the increase of tet36, tetG, tetA, tetM and tetC.
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The extensive application of antibiotics, and the occurrence and spread of antibiotic resistance genes (ARGs) shade health risks to human and animal. The long-term effects of sulfamethoxazole (SMX) and tetracycline (TC) on denitrification process were evaluated in this study, with the focus on nitrogen removal performance, microbial community and ARGs. Results showed that low-concentration SMX and TC (<0.2 mg L⁻¹) initially caused a deterioration in nitrogen removal performance, while higher concentrations (0.4–20 mg L⁻¹) of both antibiotics had no further inhibitory influences. The abundances of ARGs in both systems generally increased during the whole period, and most of them had significant correlations with intI1, especially efflux-pump genes. Castellaniella, which was the dominant genus under antibiotic pressure, might be potential resistant bacteria. These findings provide an insight into the toxic effects of different antibiotics on denitrification process, and guides future efforts to control antibiotics pollution in ecosystems.
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This study investigated the effects of tylosin (0, 10, and 100 mg/kg dry weight) on the denitrification genes and microbial community during the anaerobic digestion of cattle manure. N2 emissions were reduced and N2O emissions were increased by 10 mg/kg tylosin. Adding 100 mg/kg tylosin increased the emission of both N2O and N2. The different responses of denitrifying bacteria and genes to tylosin may have been due to the presence of antibiotic resistance genes (ARGs). Network analysis indicated that denitrification genes and ARGs had the same potential host bacteria. intI1 was more important for the horizontal transfer of denitrification genes and ARGs during anaerobic digestion than intI2. The anaerobic digestion of manure containing tylosin may increase nitrogen losses and the associated ecological risk.
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Wastewater treatment plants (WWTPs) are a source and reservoir for subsequent spread of various antibiotic resistance genes (ARGs). However, little is known about the activity and hosts of ARGs in WWTPs. Here, we utilized both metagenomic and metatranscriptomic approaches to comprehensively reveal the diversity, abundance , expression and hosts of ARGs in activated sludge (AS) from three conventional WWTPs in Taiwan. Based on deep sequencing data and a custom-made ARG database, a total of 360 ARGs associated with 24 classes of antibiotics were identified from the three AS metagenomes, with an abundance range of 7.06 × 10 −1-1.20 × 10 −4 copies of ARG/copy of 16S rRNA gene. Differential coverage binning analysis revealed that > 22 bacterial phyla were the putative hosts of the identified ARGs. Surprisingly, genus Mycobacterium and family Burkholderiaceae were observed as multi-drug resistant harboring 14 and 50 ARGs. Metatranscriptome analysis showed 65.8% of the identified ARGs were being expressed, highlighting that ARGs were not only present, but also transcriptionally active in AS. Remarkably, 110 identified ARGs were annotated as plasmid-associated and displayed a close to twofold increased likelihood of being transcriptionally expressed compared to those ARGs found exclusively within bacterial chromosomes. Further analysis showed the transcript abundance of aminoglycoside, sulfonamide, and tetracycline resistance genes was mainly contributed by plasmid-borne ARGs. Our approach allowed us to specifically link ARGs to their transcripts and genetic context, providing a comprehensive insight into the prevalence, expression and hosts of ARGs in AS. Overall, results of this study enhance our understanding of the distribution and dissemination of ARGs in WWTPs, which benefits environmental risk assessment and management of ARB and ARGs.
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Wastewater treatment plants (WWTPs) are implicated as hotspots for the dissemination of antibacterial resistance into the environment. However, the in situ processes governing removal, persistence, and evolution of resistance genes during wastewater treatment remain poorly understood. Here, we used quantitative metagenomic and metatranscriptomic approaches to achieve a broad-spectrum view of the flow and expression of genes related to antibacterial resistance to over 20 classes of antibiotics, 65 biocides, and 22 metals. All compartments of 12 WWTPs share persistent resistance genes with detectable transcriptional activities that were comparatively higher in the secondary effluent, where mobility genes also show higher relative abundance and expression ratios. The richness and abundance of resistance genes vary greatly across metagenomes from different treatment compartments, and their relative and absolute abundances correlate with bacterial community composition and biomass concentration. No strong drivers of resistome composition could be identified among the chemical stressors analyzed, although the sub-inhibitory concentration (hundreds of ng/L) of macrolide antibiotics in wastewater correlates with macrolide and vancomycin resistance genes. Contig-based analysis shows considerable co-localization between resistance and mobility genes and implies a history of substantial horizontal resistance transfer involving human bacterial pathogens. Based on these findings, we propose future inclusion of mobility incidence (M%) and host pathogenicity of antibiotic resistance genes in their quantitative health risk ranking models with an ultimate goal to assess the biological significance of wastewater resistomes with regard to disease control in humans or domestic livestock.
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Motivation: The nitrogen (N) cycle is a collection of important biogeochemical pathways in the Earth ecosystem and has gained extensive foci in ecology and environmental studies. Currently, shotgun metagenome sequencing has been widely applied to explore gene families responsible for N cycle processes. However, there are problems in applying publically available orthology databases to profile N cycle gene families in shotgun metagenomes, such as inefficient database searching, unspecific orthology groups, and low coverage of N cycle genes and/or gene (sub)families. Results: To solve these issues, this study built a manually curated integrative database (NCycDB) for fast and accurate profiling of N cycle gene (sub)families from shotgun metagenome sequencing data. NCycDB contains a total of 68 gene (sub)families and covers eight N cycle processes with 84,759 and 219,146 representative sequences at 95% and 100% identity cutoffs, respectively. We also identified 1,958 homologous orthology groups and included corresponding sequences in the database to avoid false positive assignments due to "small database" issues. We applied NCycDB to characterize N cycle gene (sub)families in 52 shotgun metagenomes from the Global Ocean Sampling expedition. Further analysis showed that the structure and composition of N cycle gene families were most strongly correlated with latitude and temperature. NCycDB is expected to facilitate N cycle studies via shotgun metagenome sequencing approaches in various environments. The framework developed in this study can be served as a good reference to build similar knowledge-based functional gene databases in various processes and pathways. Availability: NCycDB database files are available at https://github.com/qichao1984/NCyc. Supplementary information: Supplementary data are available at Bioinformatics online.
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Understanding diversity and assembly patterns of microbial communities in activated sludge (AS) is pivotal for addressing fundamental ecological questions and wastewater treatment engineering. Recent applications of molecular methods especially next generation sequencing (NGS) have led to the explosion of information about AS community diversity, including the identification of uncultured taxa, and characterization of low-abundance but environmentally important populations such as antibiotic resistant bacteria and pathogens. Those progresses have facilitated the leverage of ecological theories in describing AS community assembly. The lognormal species abundance curve has been applied to estimate AS microbial richness. Taxa-area and taxa-time relationships (TAR and TTR) have been observed for AS microbial communities. Core AS microbial communities have been identified. Meanwhile, the roles of both deterministic and stochastic processes in shaping AS community structures have been examined. Nonetheless, it remains challenging to define tempo-spatial scales for reliable identification of community turnover, and find tight links between AS microbial structure and wastewater treatment plant (WWTP) functions. To solve those issues, we expect that future research will focus on identifying active functional populations in AS using omics- methods integrated with stable-isotope probing (SIP) with the development of bioinformatics tools. Developing mathematic models to understand AS community structures and utilize information on AS community to predict the performance of WWTPs will also be vital for advancing knowledge of AS microbial ecology and environmental engineering.
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The recent recovery of genomes for organisms from phyla with no isolated representative (candidate phyla) via cultivation-independent genomics enabled delineation of major new microbial lineages, namely the bacterial candidate phyla radiation (CPR), DPANN archaea, and Asgard archaea. CPR and DPANN organisms are inferred to be mostly symbionts, and some are episymbionts of other microbial community members. Asgard genomes encode typically eukaryotic systems, and their inclusion in phylogenetic analyses results in placement of eukaryotes as a branch within Archaea. Here, we illustrate how new genomes have changed the structure of the tree of life and altered our understanding of biology, evolution, and metabolic roles in biogeochemical processes.
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Nitrogen is an essential component of all living organisms and the main nutrient limiting life on our planet. Its availability depends on diverse nitrogen-transforming reactions that are carried out by microorganisms. Nitrogen-transforming microorganisms are metabolically versatile, rendering their classification as mere nitrifiers, denitrifiers and similar classes inadequate. The classical nitrogen cycle consisting of distinct processes that follow each other in an orderly fashion does not exist. In nature, microorganisms form complex networks that link nitrogen-transforming reactions. Microbial nitrogen-transforming networks both attenuate and exacerbate human-induced global change. They produce and consume the powerful greenhouse gas nitrous oxide, lead to eutrophication of aquatic systems and, at the same time, remove nitrogen from wastewater. There are still many undiscovered nitrogen-transforming reactions that are thermodynamically feasible. The microorganisms catalysing these reactions and the involved biochemical pathways are waiting to be discovered.
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Waste water and waste water treatment plants can act as reservoirs and environmental suppliers of antibiotic resistance. They have also been proposed to be hotspots for horizontal gene transfer, enabling the spread of antibiotic resistance genes between different bacterial species. Waste water contains antibiotics, disinfectants, and metals which can form a selection pressure for antibiotic resistance, even in low concentrations. Our knowledge of antibiotic resistance in waste water has increased tremendously in the past few years with advances in the molecular methods available. However, there are still some gaps in our knowledge on the subject, such as how active is horizontal gene transfer in waste water and what is the role of the waste water treatment plant in the environmental resistome? The purpose of this review is to briefly describe some of the main methods for studying antibiotic resistance in waste waters and the latest research and main knowledge gaps on the issue. In addition, some future research directions are proposed.
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The number of microbial genomes sequenced each year is expanding rapidly, in part due to genome-resolved metagenomic studies that routinely recover hundreds of draft-quality genomes. Rapid algorithms have been developed to comprehensively compare large genome sets, but they are not accurate with draft-quality genomes. Here we present dRep, a program that reduces the computational time for pairwise genome comparisons by sequentially applying a fast, inaccurate estimation of genome distance, and a slow, accurate measure of average nucleotide identity. dRep achieves a 28 × increase in speed with perfect recall and precision when benchmarked against previously developed algorithms. We demonstrate the use of dRep for genome recovery from time-series datasets. Each metagenome was assembled separately, and dRep was used to identify groups of essentially identical genomes and select the best genome from each replicate set. This resulted in recovery of significantly more and higher-quality genomes compared to the set recovered using co-assembly.
Article
The intensive use of antibiotics results in their continuous release into the environment and the subsequent widespread occurrence of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs). This study used Illumina high-throughput sequencing to investigate the broad-spectrum profiles of both ARGs and MGEs in activated sludge and anaerobically digested sludge from a full-scale wastewater treatment plant. A pipeline for identifying antibiotic resistance determinants was developed that consisted of four categories: gene transfer potential, ARG potential, ARGs pathway and ARGs phylogenetic origin. The metagenomic analysis showed that the activated sludge and the digested sludge exhibited different microbial communities and changes in the types and occurrence of ARGs and MGEs. In total, 42 ARGs subtypes were identified in the activated sludge, while 51 ARG subtypes were detected in the digested sludge. Additionally, MGEs including plasmids, transposons, integrons (intI1) and insertion sequences (e.g. ISSsp4, ISMsa21 and ISMba16) were abundant in the two sludge samples. The co-occurrence pattern between ARGs and microbial taxa revealed by network analysis indicated that some environmental bacteria (e.g. Clostridium and Nitrosomonas) might be potential hosts of multiple ARGs. The findings increase our understanding of WWTPs as hotspots of ARGs and MGEs, and contribute towards preventing their release into the downstream environment.
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Community assembly is a central topic in microbial ecology: how do assembly processes interact and what is the relative contribution of stochasticity and determinism? Here, we exposed replicate flow-through biofilm systems, fed with nitrite-supplemented tap water, to continuous immigration from a source community, present in the tap water, to determine the extent of selection and neutral processes in newly assembled biofilm communities at both the community and the functional guild (of nitrite-oxidizing bacteria, NOB) levels. The community composition of biofilms assembled under low and high nitrite loading was described after 40 days of complete nitrite removal. The total community assembly, as well as the NOB guild assembly were largely governed by a combination of deterministic and stochastic processes. Furthermore, we observed deterministic enrichment of certain types of NOB in the biofilms. Specifically, elevated nitrite loading selected for a single Nitrotoga representative, while lower nitrite conditions selected for a number of Nitrospira. Therefore, even when focusing on ecologically coherent ensembles, assembly is the result of complex stochastic and deterministic processes that can only be interrogated by observing multiple assemblies under controlled conditions. This article is protected by copyright. All rights reserved.
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The propagation of antibiotic resistance genes (ARGs) is an emerging health concern worldwide. Thus, it is important to understand and mitigate their occurrence in different systems. In this study, 30 ARGs that confer resistance to tetracyclines, sulfonamides, quinolones or macrolides were detected in two activated sludge wastewater treatment plants (WWTPs) in northern China. Bacteria harboring ARGs persisted through all treatment units, and survived disinfection by chlorination in greater percentages than total Bacteria (assessed by 16S rRNA genes). Although the absolute abundances of ARGs were reduced from the raw influent to the effluent by 89.0%-99.8%, considerable ARG levels [(1.0 ± 0.2) × 10(3) to (9.5 ± 1.8) × 10(5) copies/mL)] were found in WWTP effluent samples. ARGs were concentrated in the waste sludge (through settling of bacteria and sludge dewatering) at (1.5 ± 2.3) × 10(9) to (2.2 ± 2.8) × 10(11) copies/g dry weight. Twelve ARGs (tetA, tetB, tetE, tetG, tetH, tetS, tetT, tetX, sul1, sul2, qnrB, ermC) were discharged through the dewatered sludge and plant effluent at higher rates than influent values, indicating overall proliferation of resistant bacteria. Significant antibiotic concentrations (2%-50% of raw influent concentrations) remained throughout all treatment units. This apparently contributed selective pressure for ARG replication since the relative abundance of resistant bacteria (assessed by ARG/16S rRNA gene ratios) was significantly correlated to the corresponding effluent antibiotic concentrations. Similarly, the concentrations of various heavy metals (which induce a similar bacterial resistance mechanism as antibiotics - efflux pumps) were also correlated to the enrichment of some ARGs. Thus, curtailing the release of antibiotics and heavy metals to sewage systems (or enhancing their removal in pre-treatment units) may alleviate their selective pressure and mitigate ARG proliferation in WWTPs.
Chapter
The family Gallionellaceae comprises the genus Gallionella with one established type species, Gallionella ferruginea. The phylo- genetic position of Gallionellaceae, as determined by 16S-rDNA sequence comparisons, is among the b-proteobacteria. Its phy- logenetic neighbors are Methylophilaceae, Nitrosomonadaceae, and Spirillaceae. The family contains gram-negative, chemolithoautotrophic, neutrophilic, and aerobic ferrous iron- oxidizing bacteria with the ability to secrete an extracellular twisted stalk composed of numerous fibers. Gallionellaceae can be found where anaerobic groundwater containing ferrous iron reaches an environment that contains oxygen. Large amounts of stalk material are usually produced; this material attracts iron hydroxides and many trace metals, giving it a brown, macro- scopic appearance. The stalk and iron hydroxide masses formed may eventually cause severe clogging of ditches, drinking-water wells, and any other facilities utilizing iron-bearing, anaerobic groundwater. The family is relevant to biotechnological pro- cesses, as it can be used to remove ferrous iron when producing drinking water from groundwater.
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Antibiotic resistance has become a major health concern; thus, there is a growing interest in exploring the occurrence of antibiotic resistance genes (ARGs) in the environment as well as the factors that contribute to their emergence. Aquatic ecosystems provide an ideal setting for the acquisition and spread of ARGs due to the continuous pollution by antimicrobial compounds derived from anthropogenic activities. We investigated, therefore, the pollution level of a broad range of antibiotics and ARGs released from hospital and urban wastewaters, their removal through a wastewater treatment plant (WWTP) and their presence in the receiving river. Several antimicrobial compounds were detected in all water samples collected. Among antibiotic families, fluoroquinolones were detected at the highest concentration, especially in hospital effluent samples. Although good removal efficiency by treatment processes was observed for several antimicrobial compounds, most antibiotics were still present in WWTP effluents. The results also revealed that copy numbers of ARGs, such as blaTEM (resistance to β-lactams), qnrS (reduced susceptibility to fluoroquinolones), ermB (resistance to macrolides), sulI (resistance to sulfonamides) and tetW (resistance to tetracyclines), were detected at the highest concentrations in hospital effluent and WWTP influent samples. Although there was a significant reduction in copy numbers of these ARGs in WWTP effluent samples, this reduction was not uniform across analyzed ARGs. Relative concentration of ermB and tetW genes decreased as a result of wastewater treatment, whereas increased in the case of blaTEM, sulI and qnrS genes. The incomplete removal of antibiotics and ARGs in WWTP severely affected the receiving river, where both types of emerging pollutants were found at higher concentration in downstream waters than in samples collected upstream from the discharge point. Taken together, our findings demonstrate a widespread occurrence of antibiotics and ARGs in urban and hospital wastewater and how these effluents, even after treatment, contribute to the spread of these emerging pollutants in the aquatic environment.
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The alignment of sequencing reads against a protein reference database is a major computational bottleneck in metagenomics and data-intensive evolutionary projects. Although recent tools offer improved performance over the gold standard BLASTX, they exhibit only a modest speedup or low sensitivity. We introduce DIAMOND, an open-source algorithm based on double indexing that is 20,000 times faster than BLASTX on short reads and has a similar degree of sensitivity. © 2014 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.
Article
Metagenomic technique was employed to characterize the seasonal dynamics of activated sludge (AS) communities in a municipal wastewater treatment plant (WWTP) over 4 years. The results indicated that contrary to Eukaryota (mainly Rotifera and Nematoda), abundances of Bacteria and Archaea (mainly Euryarchaeota) were significantly higher in winter than summer. Two-way analysis of variance and canonical correspondence analysis revealed that many functionally important genera followed strong seasonal variation patterns driven by temperature and salinity gradients; among them, two nitrifying bacteria, Nitrospira and Nitrosomonas, displayed much higher abundances in summer, whereas phosphate-removing genus Tetrasphaera, denitrifier Paracoccus and potential human faecal bacteria, i.e. Bifidobacterium, Dorea and Ruminococcus, showed significantly higher abundances in winter. Particularly, occurrence of dual variation patterns beyond explanation merely by seasonality indicated that multivariables (e.g. dissolved oxygen, sludge retention time, nutrients) participated in shaping AS community structure. However, SEED subsystems annotation showed that functional categories in AS showed no significant difference between summer and winter, indicating that compared with its microbial components, the functional profiles of AS were much more stable. Taken together, our study provides novel insights into the microbial community variations in AS and discloses their correlations with influential factors in WWTPs.
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Activated sludge (AS), which has been in use for 100 years, has been the most popular biological process in various wastewater treatment plants (WWTPs), in which bacteria plays central roles in pollutant removal. However, the potential relationship between bacteria taxa and the niches occupied by specific functional bacteria in AS are largely unknown. Here, correlation-based network analysis was applied to a 16S rRNA gene pyrosequencing dataset containing >760,000 sequences of 50 AS samples from globally distributed full-scale WWTPs. The results showed that (I) bacterial assembly in AS was nonrandomly arranged by taxonomic relatedness and (II) intra- and inter-phylum/class co-occurrence higher than expected by chance was induced by multiple deterministic processes, such as habitat filtering and competition. Moreover, based on bacterial occupancy, a prevalent core set of cosmopolitan functional bacteria (e.g., multiple nitrogen-cycling-related bacteria) was widely distributed in the AS of different WWTPs, showing strong ecological associations among them. Additionally, the AS network has statistical and structural characteristics similar to those of previously reported ecological networks, such as power-law connectivity distribution and nonrandomly connected properties. Overall, this work provides novel insights into the bacterial associations within activated sludge and sheds light on the ecological rules guiding bacterial assembly in WWTPs.
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Human sewage pollution is a major threat to public health because sewage always comes with pathogens. Human sewage is usually received and treated by wastewater treatment plants (WWTPs) to control pathogenic risks and ameliorate environmental health. However, untreated sewage that flows into water environments may cause serious waterborne diseases, as reported in India and Bangladesh. To examine the fate of the human sewage microbiome in a local municipal WWTP of Hong Kong, we used massively parallel sequencing of 16S rRNA gene to systematically profile microbial communities in samples from three sections (i.e., influent, activated sludge, and effluent) obtained monthly throughout 1 year. The results indicated that: (1) influent sewage bacterial profile reflected the human microbiome; (2) human gut bacterial community was the dominant force shaping influent sewage bacterial profile; (3) most human sewage bacteria could be effectively removed by the WWTP; (4) a total of 75 genera were profiled as potentially pathogenic bacteria, most of which were still present in the effluent although at a very low level; (5) a grouped pattern of bacterial community was observed among the same section samples but a dispersed pattern was found among the different section samples; and (6) activated sludge was less affected by the influent sewage bacteria, but it showed a significant impact on the effluent bacteria. All of these findings provide novel insights toward a mechanistic understanding of the fate of human sewage microbiome in the WWTP.
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Next generation sequencing-enabled metatranscriptomic and metagenomic datasets are providing unprecedented insights into the functional diversity of microbial communities, allowing detection of the genes present in a community as well as differentiation of those being actively transcribed. An emerging challenge of meta-omics approaches is how to quantitatively compare metagenomes and metatranscriptomes collected across spatial and temporal scales, or among treatments in experimental manipulations. Here, we describe the use of internal DNA and mRNA standards in meta-omics methodologies, and highlight how data collected in an absolute framework (per L or per cell) provides increased comparative power and insight into underlying causes of differences between samples.